Question

我在R中有一个看起来像这样的表：

"Dimension","Config","Result"
"3","1","6.43547800901942e-12"
"3","1","3.10671396584125e-15"
"3","1","5.86997050075184e-07"
"3","2","1.57865350726808"
"3","2","0.125293574811717"
"3","2","0.096173751923243"
"4","1","3.33845065295529e-08"
"4","1","4.57511389653726e-07"
"4","1","2.58918409465438e-07"
"4","2","3.23375251723051"
"4","2","2.13142950121767"
"4","2","0.510008166587752"

可以看出，我每个维度总是有6个值，而对于每个维度，我分别有3个值的配置1和3个值的配置2。是否可以“双重汇总”此表，以便输出每个维度的配置1的平均值以及每个维度的config 2的平均值？

如果我使用以下命令行：

a <- aggregate(d[,3], list(d$Dimension), mean)

我得到这个结果：

   Group.1            x
1        3 3.000202e-01
2        4 9.791985e-01

但是我想要这样的东西：

   Group.1  Config              x
1        3       1   <mean value for this row>
2        3       2   <mean value for this row>
3        4       1   <mean value for this row>
4        4       2   <mean value for this row>

Answer 1

您可以使用公式界面。

d <- read.table(text="Dimension,Config,Result
                3,1,6.43547800901942e-12
                3,1,3.10671396584125e-15
                3,1,5.86997050075184e-07
                3,2,1.57865350726808
                3,2,0.125293574811717
                3,2,0.096173751923243
                4,1,3.33845065295529e-08
                4,1,4.57511389653726e-07
                4,1,2.58918409465438e-07
                4,2,3.23375251723051
                4,2,2.13142950121767
                4,2,0.510008166587752", header=T, sep=',')

aggregate(Result ~ Dimension+Config, data=d, mean) 
  Dimension Config       Result
1         3      1 1.956678e-07
2         4      1 2.499381e-07
3         3      2 6.000403e-01
4         4      2 1.958397e+00

计算R表中不同值的平均值

1 个答案: